What Data for This Category Looks Like
This category’s data primarily comes from uploaded audio files, annotation results exported from annotation platforms, custom term lists, and spot-check samples. Daily supporting documents include transcription specifications, audio batch lists, quality inspection reports, and speaker annotation forms. Data update frequency is adjusted daily or per batch task cycle. Core fields include audio duration, transcribed text content, speaker identifiers, and quality inspection confidence levels. Units are flexibly adjusted based on the annotation task type.
Constraints Imposed by These Characteristics on Workflow Orchestration
Multi-source data access requires the workflow to use multiple types of input nodes. These nodes connect to audio upload interfaces, annotation platform APIs, and term list storage repositories respectively. Data updated daily or per batch needs trigger rules—either scheduled or batch-based—to avoid reprocessing old data. Paths and parameters for multiple supporting documents must be managed uniformly via variables to prevent inconsistencies between nodes. Time-consuming noise judgment and speaker differentiation steps need pre-check nodes. These nodes intercept invalid audio clips and reduce subsequent invalid computations. When cyclically calling annotation platform interfaces, match the platform’s call frequency limits to avoid triggering rate-limiting rules.
How to Configure Settings
The following configuration items are based on the workflow orchestration interface of FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Global variable binding | Bind the variables field to store batch ID, audio path, and term list version | Uniformly manage associated parameters for multi-source data, avoid configuration deviations between nodes |
| Trigger rule setup | Trigger by batch ID or scheduled trigger at 2:00 AM daily | Match the rhythm of daily or batch data updates, avoid repeated processing of historical data |
| Pre-check node configuration | Configure audio duration filtering and noise clip recognition rules | Intercept invalid audio, reduce invalid computations for subsequent transcription and annotation |
| Cyclic call node settings | Bind nodeId to the annotation platform interface node, set request interval to 10-30 seconds | Adapt to the call limits of the annotation platform API, prevent triggering rate limiting |
| Result classified storage | Store output files classified by quality inspection reports and speaker annotation forms | Match the archiving requirements of daily documents, facilitate subsequent operational summary |
Three Common Configuration Errors
- The JSON output from the workflow text extraction node is empty. This occurs because the node’s data source binding is not configured, or the incoming audio file format is not supported, resulting in no valid content generated during extraction.
- The specified component’s output does not appear in the workflow global variable history. This occurs because the node’s variable storage switch is not enabled, or the output result is not mapped to the specified field in
variables. - Rate limiting errors are triggered when cyclically calling HTTP interfaces in the workflow. This occurs because no request interval is set, or the interval is set too short, exceeding the call frequency limits of the connected platform.
How to Verify a Successful Configuration
- Manually trigger a test batch to confirm input nodes correctly pull specified audio files and term list content.
- Open the global variable panel to verify the specified node’s output is successfully mapped to the corresponding field in
variables. - Submit one test data entry to confirm the pre-check node intercepts non-compliant audio clips.
- Review workflow run logs to confirm cyclic HTTP interface call intervals fall within the preset 10-30 second range.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.